Systems and methods for generation and selection of access rules

ABSTRACT

A resource security system may generate access rules for use in determining whether to grant or deny a request for access to a resource. In order to generate the access rules, the resource security system may select certain access request parameters and determine conditions associated with those parameters. The resource security system may generate mutually exclusive segments associated with a condition of each of the parameters. The resource security system may generate independent access rules based on the segments. The resource security system may then evaluate the performance of each of the access rules based on validity information corresponding to previously received access requests that satisfy the conditions of a particular access rule.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.15/365,389, filed on Nov. 30, 2016 and titled “SYSTEMS AND METHODS FORGENERATION AND SELECTION OF ACCESS RULES,” the entire contents of theabove applications are hereby incorporated by reference for all purposesin its entirety.

BACKGROUND

An unauthorized user may fraudulently request access to a resource usingthe authorization information of an authorized user. To prevent suchfraudulent access, a resource security system may implement access rulesto reject access requests having certain parameters that are indicativeof fraud. However, in response to being denied access, the unauthorizeduser may change their method for making fraudulent access requests,thereby changing the parameters, in order to avoid rejection by theaccess rules. In addition, authorized users may also change theirmethods for making legitimate access requests over time. Consequently,the performance of the access rules may degrade over time, increasinglydenying access to authorized users or increasingly granting access tounauthorized users. Therefore, the access rules may periodically bechanged or updated, which may take a significant amount of time andcomputing resources. Accordingly, there is a need for improved systemsand methods for securing access to resources.

BRIEF SUMMARY

A resource security system may generate access rules for use indetermining whether to grant or deny a request for access to a resource.In order to generate the access rules, the resource security system mayselect certain access request parameters and determine conditionsassociated with those parameters. The resource security system maygenerate mutually exclusive segments associated with a condition of eachof the parameters. The resource security system may generate independentaccess rules based on the segments. The resource security system maythen evaluate the performance of each of the access rules based onvalidity information corresponding to previously received accessrequests that satisfy the conditions of a particular access rule.

Other embodiments are directed to systems, devices, and computerreadable media associated with methods described herein.

A better understanding of the nature and advantages of embodiments ofthe present invention may be gained with reference to the followingdetailed description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a resource security system for providing access toresources, in accordance with some embodiments.

FIG. 2 shows a functional block diagram of an access server fordetermining an access request outcome while performing rule evaluation,in accordance with some embodiments.

FIG. 3 shows a functional block diagram of an access rule generationsystem for generating and selecting access rules using a decision tree,in accordance with some embodiments.

FIG. 4 shows an exemplary decision tree for generating access rules, inaccordance with some embodiments.

FIG. 5 shows a functional block diagram of an access rule generationsystem for generating and selecting access rules using segmentation, inaccordance with some embodiments.

FIG. 6 shows an exemplary segmentation diagram for generating andselecting access rules, in accordance with some embodiments.

FIG. 7 shows a flowchart of a method for generating and selecting accessrules using a computer system, in accordance with some embodiments.

FIG. 8 shows a functional block diagram of components of an exemplarycomputer system including an access rule generation system and an accessserver, in accordance with some embodiments.

TERMS

Prior to discussing embodiments of the invention, description of someterms may be helpful in understanding embodiments of the invention.

The term “resource” generally refers to any asset that may be used orconsumed. For example, the resource may be an electronic resource (e.g.,stored data, received data, a computer account, a network-based account,an email inbox), a physical resource (e.g., a tangible object, abuilding, a safe, or a physical location), or other electroniccommunications between computers (e.g., a communication signalcorresponding to an account for performing a transaction).

The term “access request” generally refers to a request to access aresource. The access request may be received from a requesting computer,a user device, or a resource computer, for example. The access requestmay include authorization information, such as a user name, accountnumber, or password. The access request may also include and accessrequest parameters.

The term “access request parameter” generally refers to informationabout the access request and when or how it was made. For example, theparameters of an access request may include one or more of: the timethat the access request was received, the day of the week that theaccess request was received, the source-location of the access request,the amount of resources requested, an identifier of the resource beingrequest, an identifier of a user, an identifier of an access device, anidentifier of a user device, an identifier of a request computer, alocation of the user, a location of the access device, a location of theuser device, a location of the request computer, an indication of when,where, or how the access request is received by the resource computer,an indication of when, where, or how the access request is sent by theuser or the user device, an indication of the requested use of theresource, and an indication of the type, status, amount, or form of theresource being requested. Access request information may be stored foreach access request received by a resource computer. As furtherdescribed herein, access rules include conditions that may be satisfiedby certain parameter values.

The term “access rule” may include any procedure or definition used todetermine an access rule outcome for an access request based on certaincriteria. In some embodiments, the rule may comprise one or more ruleconditions and an associated rule outcome. A “rule condition” mayspecify a logical expression describing the circumstances under whichthe outcome is determined for the rule. A condition of the access rulemay be involved by an access request parameter based on the parameterhaving a specific parameter value, based on the parameter value beingwithin a certain range, based on the parameter value being above orbelow a threshold, or any combination thereof.

A “segment” may represent one or more access rule conditions associatedwith parameters of an access request. The access rule conditions of a“segment” are mutually exclusive to the access rule conditions of othersegments. That is, the conditions are independent. A segmentationdiagram having a plurality of segments may be used to representconditions for potential access rules and previous access requestssatisfying those conditions. Since each segment is independent, thefraud detection performance of each segment may be determinedsimultaneously and in parallel.

An “access rule outcome” of an access rule may represent an outcomedetermined by that rule based on one or more conditions of the rule andthe parameters of the access request. For example, an access rule mayprovide an access rule outcome of either “reject,” “accept,” or“review,” when its conditions are involved by an access request.

The term “access request outcome” may include any determination ofwhether to grant access to the resource. The access request outcomes mayinclude “accept,” “reject,” or “review.” In some embodiments, an accessrequest outcome for an access request may be “reject” if any of theaccess rules have an access rule outcome of “reject.” In someembodiments, an access request outcome for an access request may be“accept” if any of the access rules have an access rule outcome of“accept,” regardless of any outcome being “reject.” An access requestoutcome of “accept” may cause the access request to be granted. Anaccess request outcome of “reject” may cause the access request to bedenied. The “review” outcome may initiate a review process for theaccess request. In various embodiments, other outcomes or other meaningsof these outcomes may be used.

The term “predictive percentage” refers to the percentage of accessrequests triggering an access rule that are predicted to be fraudulent.The fraud predictive percentage may be determined based on reports offraudulent (e.g., invalid or unauthorized) access requests. predictivepercentage For example, if an access rule is triggered by 100 accessrequests within a certain time period and 90 of those access requestsare reported to be fraudulent, then the predictive percentage of theaccess rule for that time period is 90% (e.g., 90±100).

The term “reporting” generally refers to a process for identifyingwhether an access request was fraudulent or legitimate. Reporting mayinvolve a user of a resource reporting fraudulent use to the owner oroperator of the resource. For example, an owner of a payment account mayinitiate a charge-back for a fraudulent transaction on their account. Inanother example, a user of an email account may report a certain emailas being “junk” or “spam” mail. In some situations, an authorized userof a resource may report a denial of access to the resource. Forexample, a user may report that a legitimate transaction was denied, orthe user may report that an email is “not-spam.” Such reporting may beused to determine or adjust validity information (e.g., valid/legitimateor invalid/fraudulent) for the corresponding access request. Forexample, if a report of fraudulent access to a resource is received, thevalidity information corresponding to the access request which grantedaccess may be updated to indicate that the access request wasfraudulent.

The term “server computer” may include a powerful computer or cluster ofcomputers. For example, the server computer can be a large mainframe, aminicomputer cluster, or a group of computers functioning as a unit. Inone example, the server computer may be a database server coupled to aweb server. The server computer may be coupled to a database and mayinclude any hardware, software, other logic, or combination of thepreceding for servicing the requests from one or more other computers.The term “computer system” may generally refer to a system including oneor more server computers coupled to one or more databases.

As used herein, the term “providing” may include sending, transmitting,making available on a web page, for downloading, through an application,displaying or rendering, or any other suitable method. In variousembodiments of the invention, rule profiles, rule outcome frequencies,and rule outcome disposition frequencies may be provided in any suitablemanner.

DETAILED DESCRIPTION

A resource security system may be used to grant or deny access toresources. In addition, the resource security system may implementaccess rules to reject access requests having parameters indicative offraud. If fraudulent access does occur, it may be reported and theresource security system may evaluate the performance of the accessrules based on the reports. For instance, the resource security systemmay use the reports to determine the percentage of false positivesproduced by the access rules and adjust the validity informationaccordingly.

Periodically, the resource security system may change or update theaccess rules based on their performance. To generate an updated set ofcandidate access rules, the resource security system may select certainparameters of the access request parameters and generate a plurality ofpotential access rules by segmenting the selected parameters into aplurality of conditions. The resource security system may then evaluatethe mutually exclusive segments independently and in parallel, therebyquickly and efficiently generating a set of updated candidate accessrules which are selected from the potential access rules.

I. Resource Security System

A resource security system may receive requests to access a resource. Inorder to determine whether an access request is fraudulent, the resourcesecurity system may include an access server for determining an outcomefor the access request based on access rules. The resource securitysystem may also include an access rule generation system for generatingand selecting the access rules to be implemented by the access server.The resource security system is described in further detail below.

A. Resource Security System for Securing Access to a Resource

FIG. 1 shows a resource security system 100 for providing access toresources, in accordance with some embodiments. The arrows shown in FIG.1 represent the flow of information between the various elements of theresource security system 100. The resource security system 100 may beused to provide authorized users access to a resource while denyingaccess to unauthorized users. In addition, the resource security system100 may be used to deny fraudulent access requests that appear to belegitimate access requests of authorized users. The resource securitysystem 100 may implement access rules 122 to identify fraudulent accessrequests based on the parameters of the access request. The resourcesecurity system 100 may periodically update the access rules 122 basedon their performance.

The resource security system 100 includes a resource computer 110. Theresource computer 110 may control access to a physical resource 118,such as a building or a lockbox, or an electronic resource 116, such asa local computer account, a digital file or document, a networkdatabase, an email inbox, a payment account, or a website login. In someembodiments, the resource computer may be a webserver, an email server,or a server of an account issuer. The resource computer 110 may receivean access request from a user 140 via a user device 150 (e.g., acomputer or a mobile phone) of the user 140. The resource computer 110may also receive the access request from the user 140 via a requestcomputer 170 coupled with an access device 160 (e.g., a keypad or aterminal). In some embodiments, the request computer 170 may be aservice provider that is different from a resource provider that owns oroperates the resource computer 110.

The access device 160 and the user device 150 may include a user inputinterface such as a keypad, a keyboard, a finger print reader, a retinascanner, a biometric reader, a magnetic stripe reader, a chip cardreader, a radio frequency identification interface, or a wireless orcontactless communication interface, for example. The user 140 may inputauthorization information into the access device 160 or the user device150 to access the resource. The authorization information may includeone or more of a user name, an account number, a token, a password, apersonal identification number, a signature, and a digital certificate,for example. In response to receiving authorization information input bythe user 140, the user device 150 or the request computer 170 may sendan access request to the resource computer 110 along with one or moreparameters of the access request. The access request may include theauthorization information provided by the user 140.

In one example, the user 140 may enter one or more of an account number,a personal identification number, and password into the access device160 to request access to a physical resource (e.g., to open a lockedsecurity door in order to access a building or a lockbox) and therequest computer 170 may generate and send an access request to theresource computer 110 to request access to that resource. In anotherexample, the user 140 may operate the user device 150 to input a username and password as a request for the resource computer 110 to provideaccess to an electronic resource 116 (e.g., a website login or a file)that is hosted by the resource computer 110. In another example, theuser device 150 may send data or information (e.g., an email) to requestthe resource computer 110 (e.g., an email server) to provide the data orinformation access to an electronic resource 116 (e.g., deliver theemail to an inbox). In another example, the user 140 may provide anaccount number and/or a personal identification number to an accessdevice 160 in order to request access to a resource (e.g., a paymentaccount) for conducting a transaction. The resource computer 110 mayalso receive access requests in other manners.

In some embodiments, the resource computer 110 may verify theauthorization information of the access request based on informationstored at the request computer 170. In other embodiments, the requestcomputer 170 may verify the authorization information of the accessrequest based on information stored at the resource computer 110. Theresource computer 110 may grant or deny access to the resource based onthe verification of the authorization information.

The resource computer 110 may receive the access request substantiallyin real-time, accounting for delays computer processing and electroniccommunication. Once the access request is received, the resourcecomputer 110 may determine parameters of the access request. In someembodiments, the parameters may be provided by the user device 150 orthe request computer 170. For example, the parameters of the accessrequest may include one or more of: a time that the access request wasreceived, a day of the week that the access request was received, thesource-location of the access request, the amount of resourcesrequested, an identifier of the resource being request, an identifier ofthe user 140, an identifier of the access device 160, an identifier ofthe user device 150, an identifier of the request computer 170, alocation of the user 140, a location of the access device 160, alocation of the user device 150, a location of the request computer 170,an indication of when, where, or how the access request is received bythe resource computer 110, an indication of when, where, or how theaccess request is sent by the user 140 or the user device 150, anindication of the requested use of the electronic resource 116 or thephysical resource 118, and an indication of the type, status, amount, orform of the resource being requested. In other embodiments, the requestcomputer 170 or the access server 120 may determine the parameters ofthe access request.

While the resource computer 110 may determine that an access requestincludes proper authentication information, the resource computer 110may send the parameters of the access request to the access server 120in order to determine whether the access request is fraudulent. Theaccess server 120 may store one or more access rules 122 for identifyingfraudulent access requests in a system memory of the access server 120.Each of the access rules 122 may include one or more conditionscorresponding to one or more parameters of the access request. Theaccess server 120 may determine an access request outcome indicatingwhether the access request should be accepted (e.g., access to theresource granted), rejected (e.g., access to the resource denied), orreviewed by comparing the access rules 122 to the parameters of theaccess request as further described below. In some embodiments, insteadof determining an access request outcome, the access server 120 maydetermine an evaluation score based on outcomes of the access rules. Theevaluation score may indicate the risk or likelihood of the accessrequire being fraudulent. If the evaluation score indicates that theaccess request is likely to be fraudulent, then the access server 120may reject the access request.

The access server 120 may send an indication of the access requestoutcome to the resource computer 110 (e.g., accept, reject, or review).In some embodiments, the access server 120 may send the evaluation scoreto the resource computer 110 instead. The resource computer 110 may thengrant or deny access to the resource based on the indication of theaccess request outcome or the evaluation score. For instance, if theaccess request outcome or the evaluation score received from the accessserver 120 indicates “accept,” then the resource computer 110 mayprovide the user 140 or the user device 150 access to the resource. Ifthe access request outcome or the evaluation score received from theaccess server 120 indicates “reject,” then the resource computer 110 maynot provide the user 140 or the user device 150 access to the resource.If the access request outcome or the evaluation score indicates“review,” then the resource computer 110 may initiate a review processfor the access request. The review process may involve contacting theuser 140 or another entity involved in requesting access (e.g., theresource provider or another service provider).

In some embodiments, the access server 120 may be remotely accessed by auser. Remote access to the access server 120 may provide for both realtime and offline monitoring of the operational set of access rules real.For example, the access rule triggering and the predictive powerperformances may be monitored. The access server 120 may store accessrequest and access rule data and logs in a secure environment andimplement user privileges and user role management for accessingdifferent types of stored data. For example, user privileges may be setto enable users to perform one or more of the following operations: viewlogs of received access request, view logs of access request outcomes,enable or disable the execution of the access rules 122, update ormodify the access rules 122, change certain access request outcomes.Different privileges may be set for different users.

In order to evaluate the performance of the access rules, the resourcecomputer 110 may store access request information for each of the accessrequests that it receives. The access request information may includethe parameters of each of the access requests and an indication of theaccess request outcome for the access request. The resource computer 110may also store validity information corresponding to each accessrequest. The validity information may indicate whether the accessrequest was legitimate or fraudulent. The validity informationassociated with an access request may initially be based on thecorresponding access request outcome. For instance, the validityinformation may indicate that an access request is legitimate and that arejected access request is fraudulent. The validity information may beupdated based on reports received for that access request or based on areview process for that access request. In some embodiments, the accessserver 120 or the request computer 170 may generate and store the accessrequest information and the validity information.

The access rules 122 implemented by the access server 120 may begenerated by an access rule generation system 130. In some embodiments,the functions of the access server 120 and the access rule generationsystem 130 may be performed by the same server or servers. The accessrule generation system 130 may generate candidate access rules 134 forthe access server 120 based on the access request information and thevalidity information. The access rules 122 implemented by the accessserver 120 may be selected from the set of candidate access rules 134.In order to generate the candidate access rules 134, the access rulegeneration system 130 may receive the access request information and thevalidity information corresponding to the access request informationfrom the resource computer 110 or the access server 120. The access rulegeneration system 130 may generate and select the candidate access rules134 based on the access request information and the correspondingvalidity information.

The access rule generation system 130 may periodically receive new orupdated the access request information and validity information from theresource computer 110 or the access server 120. The access rulegeneration system 130 may then re-generate the candidate access rules134 based on the new or updated access request information and validityinformation. As such, the candidate access rules 134 may be based on themost recent patterns of fraudulent resource use and the most recentpatterns of legitimate resource use. The access rule generation system130 may send the new or updated candidate access rules 134 to the accessserver 120 to be implemented. The generation and selection of candidateaccess rules by an access rule generation server is further describedbelow.

B. Access Server for Determining an Access Request Outcome whilePerforming Rule Evaluation

As discussed above, a resource security system may include an accessserver that uses access rules to determine an access request outcomebased on access request parameters. The access rules implemented by theaccess server may be periodically changed or updated using candidateaccess rules received from an access rule generation system. The accessrule generation system may generate the candidate access rules based ontheir fraud detection performance. However, it may not be possible toevaluate the fraud detection performance of the access rules currentlyimplemented by the access server since those rules are used to rejectaccess requests that are determined to be fraudulent. For instance, itmay not be possible to determine whether an access request outcome of“reject” is a false positive or not when the access request is rejectedsince the false positive information may be based on reports offraudulent activity, which would not be received. As further describedbelow, an access server may accept certain access requests that would berejected by an access rule outcome in order to evaluate the performanceof that access rule based on reports received for those access requests.

FIG. 2 shows a functional block diagram of an access server 200 fordetermining an access request outcome while performing rule evaluation,in accordance with some embodiments. The access server 200 may operatesimilar to the access server 120 of FIG. 1 described above. The accessserver 200 may be used in a resource security system similar to theresource security system 100 of FIG. 1 described above. As furtherdescribed below, the access server 200 may load one or more access rules222 into a system memory of the access server and determine an accessrequest outcome or an evaluation score for an access request based onthe parameters of the access request. The access server 200 may thenprovide the access request outcome or the evaluation score back to theresource computer, which may grant or deny access to the resourceaccordingly.

First, at 201, the access server 200 may obtain the access requestparameters for a certain access request. The access request parametersmay be received from a resource computer or from a request computer overa network in real-time. For example, the access request parameters mayinclude one or more of: the time that the access request was received,the day of the week that the access request was received, thesource-location of the access request, the amount of resourcesrequested, an identifier of the resource being request, an identifier ofa user, an identifier of an access device, an identifier of a userdevice, an identifier of a request computer, a location of the user, alocation of the access device, a location of the user device, a locationof the request computer, an indication of when, where, or how the accessrequest is received by the resource computer, an indication of when,where, or how the access request is sent by the user or the user device,an indication of the requested use of the resource, and an indication ofthe type, status, amount, or form of the resource being requested. Insome embodiments, the user, the user device, the access device, or therequest computer may provide one or more of the parameters of the accessrequest.

At 202, after obtaining the access request parameters, the access server200 may determine an access rule outcome for each access rule 222. Inorder to determine the access rule outcomes, the access server 200 mayaccess the system memory of the access server 200 to obtain the accessrules 222. Each access rule 222 includes one or more conditions that maybe satisfied by a certain parameter value or range of parameter values.The access server 200 may determine an access rule outcome for aparticular access rule 222 by comparing the parameter values of theaccess request parameters to the one or more conditions of the accessrule 222. If the parameter values of the access request satisfy the oneor more conditions of that particular access rule 222, then the accessrule 222 is “triggered” by that access request and the access rule 222provides its associated access rule outcome. The access rule outcome fora particular access rule 222 may be one of “accept,” “reject,” or“review.” In some embodiments the access rule outcome may be anevaluation score indicating accept, reject, or review.

In one example of determining an access rule outcome, access requestparameters may be received for a request to access a website accountlogin. In this example. the parameters of the access request may includea “source location” indicating the geographic location of the user ordevice that is requesting access and an “authorized user location”indicating the geographic location of the authorized user of the websiteaccount. In this example, a certain access rule may have conditions thatare satisfied (e.g., triggered) when the “source location” does notmatch the “authorized user location.” Since the “source location” notmatching the “authorized user location” may be indicative of fraudulentactivity, the access rule may have an outcome of “reject” whentriggered. Accordingly, an access request coming from a location thatdoes not match the location of the authorized user may be rejected.

In another example of determining an access rule outcome, an accessrequest may be for a payment transaction and the parameters of theaccess request may include the “transaction amount” and the “shippingcountry” for shipping goods purchased in the transaction. In thisexample, a certain access rule may have conditions that are satisfiedwhen the “transaction amount” is over $1,000 and when the “shippingcountry” is a country having higher reporting of fraud. This access rulemay have an access request outcome of “reject.” Accordingly, a accessrequest for a transaction to ship goods amounting to over $1,000 to acertain country may be rejected.

In another example of determining an access rule outcome, an accessserver may obtain access request parameters for an access request todeliver an email message to an inbox. The parameters of the accessrequest may include one or more alphanumeric keywords from the emailmessage and a “source IP address” of the email message. In this example,a certain access rule may have a first condition that is satisfied whenone or more of the keywords matches one or more stored words indicativeof “spam” or fraud. The access rule may have a second condition that issatisfied when the IP address falls within a certain range of IPaddresses. Accordingly, a spam email message may not be delivered to aninbox if it contains certain keywords and is sent from a certain rangeof IP addresses.

At 203, after determining the access rule outcome for each of the accessrules 222, the access server 200 may determine an access request outcomebased on the access rule outcomes. The access request outcome mayindicate “accept,” “reject,” or “review.” In one example of determiningan access request outcome, the access server 200 may determine an accessrequest outcome of “accept” if any of the access rule outcomes are“accept.” In another example, the access server 200 may determine anaccess request outcome of “reject” if one or more of the access ruleoutcomes are “reject” and none of the access rule outcomes are “accept.”In another example, the access server 200 may determine an accessrequest outcome of “review” if one or more of the access rule outcomesare “reject” and one or more of the access rule outcomes are “accept.”In other embodiments, the access server 200 may determine an accessrequest evaluation score based on the access rule evaluation scores. Theaccess request evaluation score may indicate an outcome of “accept,”“reject,” or “review” based on threshold values.

As mentioned above, the access rules implemented by the access server200 may be evaluated in order to determine their fraud detectionperformance. At 204, the access server 200 may determine whether toaccept a particular access request in order to evaluate the performanceof the triggered access rule. For instance, if the access requestoutcome is not “reject” or “review,” the access server 200 may providean access request outcome of “accept” instead, thereby causing theaccess request to be granted which allows for fraudulent access to bereported if it occurs. By accepting the access request, a percentage offalse positives produced by the triggered access rule may be determinedbased on the reports received. For instance, an access rule having anoutcome of “reject” may be triggered by an access request that isaccepted during an evaluation process. If fraudulent access is notreported for that access request, that indicates that the triggering ofthe access rule was a false positive. Such false positive informationfor an access rule 222 may be used to adjust validity information forother access requests that triggered that same access rule 222.

At 204, the access server 200 may determine whether to evaluate thetriggered access rule based on certain criteria or thresholds. Forexample, the access server 200 may determine to perform evaluation basedon one or more of: the number of access requests received since the lastevaluation, the number of access requests that have triggered thisaccess rule since the last evaluation, the amount of time since the lastevaluation, the amount of time since the this access rule was evaluated,and a random number generator. In one example, the access server 200 mayaccept 1 in every 100 access requests that would have been rejected by acertain access rule. In another example, the access server mayautomatically accept 0.5% of all access requests based on a randomnumber generator.

If the access server 200 determined to not accept the access request aspart of an evaluation process at 204 (e.g., the decision at step 204 isNO), then the access server 200 may provide an indication of the accessrequest outcome (e.g., accept, reject, or review). The indicated of theaccess request outcome may be sent to the computer that sent the accessrequest or access request parameters to the access server 200 (e.g., theresource computer or the request computer). However, if the accessserver 200 determined to accept the access request for evaluation of thetriggered access rule (e.g., the decision at step 204 is YES), themaccess server may provide an indication that the access request outcomeis “accept,” regardless of the access request outcome determined at step203.

The access server may store evaluation information 250 regarding theaccess request and the access rule being evaluated. The evaluationinformation 250 may include identifiers of the access rules 222 beingimplemented by the access server 200. The evaluation information mayalso include records for each access request accepted during theevaluation process at 204. The records for each access request mayinclude an identifier of the access requests that was accepted, anidentifier of the triggered access rules 222, and the access requestoutcome determined at 203. The evaluation information 250 may alsoinclude an indication of the parameters of the access request that wasaccepted for evaluation of the triggered access rule.

Since patterns of fraudulent and legitimate access may change over time,the fraud detection performance of the currently implemented accessrules 222 may degrade over time. By accepting certain access requestsfor evaluation of the currently implemented access rules 222, it ispossible determine the whether those access rules are providing falsepositives as discussed above. Therefore, access rules 222 that havingpoor fraud detection performance may be updated or replaced by betterperforming access rules. Evaluation of the currently implemented accessrules is advantageous because fewer false positives means that fewerauthorized users are inadvertently denied access resources. Evaluationis also advantageous because fewer fraudulent access request aregranted, thereby improving the security of the resources.

II. Access Rule Generation and Selection Using a Decision Tree

As discussed above, a resource security system may include an accessrule generation system for generating and selecting candidate accessrules to be implemented by an access server. In some embodiments, theaccess rule generation system may generate access rules using a decisiontree or using segmentation as further described below.

FIG. 3 shows a functional block diagram of an access rule generationsystem 300 for generating and selecting access rules using a decisiontree, in accordance with some embodiments. The access rule generationsystem 300 may operate similar to the access rule generation system 130of FIG. 1. The access rule generation system 300 may be implemented in aresource security system similar to the resource security system 100 ofFIG. 1 described above.

As further described below, the access rule generation system 300 maygenerate candidate access rules 334 using a decision tree based onaccess requests previously received by an access server. The access rulegeneration system 300 generate a decision tree having nodescorresponding to certain access rule parameter conditions. The accessrule generation system 300 may then determine the performance of nodeswithin a branch of the decision tree. The performance of a branch may bebased on the validity information of access requests having parameterscorresponding to the conditions of the branch. The access rulegeneration system 300 may continue to select nodes to build the branchuntil the best performing branch is determined. The access rulegeneration system 300 may then generate a candidate access rule 334having conditions corresponding to the conditions of the branch.

The access rule generation system 300 may continue building candidateaccess rules using the decision tree. The access rule generation system300 may determine the next best performing branch by returning to ahigher node in the tree to continue evaluating performance of thebranches. After generating one or more candidate access rules 334, theaccess rule generation system 300 may provide the candidate access rules334 to an access server to be used for determining access requestoutcomes.

A. Stored Information for Use in Generating Access Rules

The access rule generation system 300 may store information that is thebasis for the access rules that are generated. The stored informationmay reflect the types of fraudulent and legitimate resource use that thegenerated access rules can identify. The access rule generation system300 may store access request information 310, validity information 320,and evaluation information 350. The access request information 310, thevalidity information 320, and the evaluation information 350 may bereceived from one or more of a resource computer, a request computer,and an access server.

The access request information 310 may include a plurality of accessrequests that were previously received by an access server. The accessrequest information 310 may include access request parameters for eachof the access requests. The access request information 310 may alsoinclude an indication of whether the access request outcome wasrejected, accepted, or reviewed.

The validity information 320 may indicate whether each access request inthe access request information 310 is legitimate or fraudulent. Forinstance, the validity information 320 may indicate that a certainaccess request of the access request information 310 was reported to befraudulent or an indication that a certain access request was reportedto be legitimate. The validity information corresponding to certainaccess request may also be based on the access request outcome for thataccess request as determined by the access server. For instance, arejected access request may initially have corresponding validityinformation indicating that the access request is fraudulent and anaccepted access request may initially have corresponding validityinformation indicating that the access request is legitimate. Thevalidity information 320 corresponding to a certain access request maybe updated over time based on a report of fraudulent access or reportsof the denial of legitimate access (e.g., a report may not be receiveduntil a later time, or additional reports for a certain access requestmay be received later).

The evaluation information 350 may include identifiers of the accessrules being implemented by the access server. The evaluation information350 may also include records for each access request accepted during anevaluation process at the access server. The records for each accessrequest includes one or more of an identifier of the access requeststhat was accepted, an identifier of the triggered access rule, and theaccess request outcome. The evaluation information 350 may also includean indication of the parameters of the access request that was acceptedfor evaluation of the triggered access rule.

B. Adjusting the Validity Information to Account for False Positives

Before generating potential access rules, at 301 the access rulegeneration system 300 may adjust the validity information 320 using theevaluation information 350. The access rule generation system 300 mayadjust the validity information 320 to account for false positives inthe access requests rejected by the access rules implemented by theaccess server. The access rule generation system 300 may determine thefalse positive percentage for a certain access rule (e.g., an accessrule implemented by an access server) based on the reports received foraccess requests triggered by that access rule (e.g., the access requestwas were accepted during an evaluation process).

In one example of adjusting the validity information, the evaluationinformation 350 may indicate that access server accepted, instead ofrejected, one hundred access requests triggered by a particular accessrule over a certain period of time. However, the validity information320 may indicate that only sixty of the access requests out of thehundred access requests have been reported as being fraudulent. In thisexample, the outcome of the access rule was a false positive 40% of thetime (e.g., 40 of 100). The access rule generation server 300 may adjustthe validity information corresponding to the access requests rejectedby that access rule to account for the access rule's 40% false positivepercentage. For instance, the access rule generation server 300 mayadjust the validity information for the corresponding access requestssuch that the validity information indicates that 40% of the accessrequests triggering the access rule are legitimate, instead offraudulent. In another example, a valid access request may be assigned avalidity score of 0.0 in the validity information 320 and a fraudulentaccess request may be assigned a validity score of 1.0. The access rulegeneration system 300 may then adjust the validity score correspondingto access requests that triggered an access rule based on the falsepositive percentage. In this example, the access rule generation system300 may assign a validity score of 0.6, instead of 1.0, to accessrequests rejected by the access rule that provides false positives 40%of the time. As such, these access requests may be considered to be 60%fraudulent instead of 100% fraudulent. The adjusted validity information(e.g., validity score) may be used by the access rule generation system300 in determining the performance of the potential access rules.

By adjusting the validity information 320 to account for falsepositives, it is possible for the access rule generation system 300 toselect access rules to replace under-performing access rules that arecurrently implemented by the access server, thereby leading to fewerfalse positives in the future. Having fewer false positives isadvantageous since, depending on the purpose and implementation of theaccess server, more accurate access rules leads to fewer users beingdenied access to their website accounts, fewer legitimate transactionsfor goods or services being denied, and fewer legitimate emails beinglabeled as “junk” email, for example. In addition, user devices and theresource computer may consume fewer network resources in the process ofrequesting access to resources since fewer legitimate access requestswill need to be re-sent due to false rejections.

The adjusted validity information may be used in the generation ofaccess rules, regardless of the method used. For example, adjustedvalidity information may be used to generate access rules using adecision tree and it may also be used to generate access rules usingsegmentation. Using a decision tree, a set of access requests maycorrespond to a certain branch of the decision tree and the adjustedvalidity information for those access requests may be used to determinethe performance of the branch. Using segmentation, a unique set ofaccess requests may correspond to a certain mutually-exclusive segmentof conditions and the adjusted validity information for those accessrequests may be used to determine the performance of the segment.

The generation of access rules using a decision tree is furtherdiscussed below with reference to FIG. 4 and the generation of accessrules using segmentation is further discussed below with reference toFIGS. 5 and 6.

C. Use of a Decision Tree in Generating Access Rules

The access rule generation system 300 may use a decision tree togenerate access rules using the process at 302-307. FIG. 4 shows anexemplary decision tree 400 for generating access rules, in accordancewith some embodiments. The decision tree 400 includes a plurality of“nodes” 401, 410-419, 420-426, and 430-433. In the decision tree 400 ofFIG. 4, the nodes are represented by circles. The decision tree 400begins at a “root” node 401 that “branches” down to a plurality of“children” nodes which are connected to the root node 401 by vertices.For instance, the nodes 410-419, which are connected to the root node401, are children of the root node 401, the nodes 420-246 are childrenof node 414, and the nodes 430-433 are children of node 421. Theinterconnected nodes moving from parents to children down the tree aregenerally referred to as a “branch” of the decision tree 400. As furtherdescribed below, a branch of the decision tree 400 may be used togenerate access rules. In the decision tree 400, the children nodes areonly connected to the parent node. The children nodes are notinterconnected to each other.

In FIG. 4, each of the nodes represents a condition of an access rule,which is indicated within the node. For example, node 414 represents thecondition X₂₂. In addition, each branch of nodes represents one or moreconditions of an access rule, which is indicated below the node. Forexample, the branch including node 414 and node 423 represents thecondition X₂₂X₃₁. In the decision tree 400, the root node 401 may notrepresent any condition. The access rule generation system 300 maydetermine the conditions of the nodes based on the access requestparameters in the access request information 310. In FIG. 4, the bestperforming nodes/branches are have solid lines and the othernodes/branches have dashed lines. For simplicity of representation, FIG.4 does not show all nodes or branches of the decision tree 400. Forinstance, the nodes of the decision tree 400 which are not shown in FIG.4 are represented by an ellipsis ( . . . ). In addition, certainbranches of the decision tree 400 are not shown in FIG. 4.

The access rule generation system 300 may use the decision tree 400 togenerate an access rule having certain conditions. The access rulegeneration system 300 may generate the decision tree 400 based on theaccess request information 310. In other embodiments, the access rulegeneration system 300 may generate a different decision tree accordingto different access request information. For example, the access requestparameters may include a parameter X₁ indicating a “day of the week”parameter for an access request. In this example, the access rulegeneration system 300 may determine seven conditions, X₁₁, X₁₂, X₁₃,X₁₄, X₁₅, X₁₆, and X₁₇, corresponding to the seven days of the weekpossible for parameter X₁. Another parameter, X₂, may indicate a“shipping state” parameter of an access request and may include fiftyconditions X₂₁ through X₂₅₀ corresponding to each of the fifty U.S.states. Another parameter, X₃, may indicate a “resource amount”parameter of an access request and may include 10 conditions X₃₁ throughX₃₁₀ corresponding to ten mutually exclusive numerical ranges ofresource amounts. The decision tree 400 may further include othernon-specified parameters conditions X_(yz).

The access rule generation system 300 may generate an access rule havingcertain conditions based on the decision tree 400. In general, adecision tree process for generating access rules may evaluate each nodein the first level down to determine the best performing node. The bestperforming node may have the fewest decision errors (e.g., “falsepositives” where a legitimate access request is determined to befraudulent and “false negatives” where a fraudulent access request isnot detected). The performance may be based on the amount or percentageof decision errors or based on the predictive percentage of theconditions of the node. Then the decision tree process makes a binarysplit at the best performing node such that the left split is a firsttree where the condition of the best performing node is satisfied andthe right split is a second tree where the condition of the bestperforming node is not satisfied. This performance evaluation andsplitting process is repeated until one or more stop criterion are met.

An example decision tree process for generating access rules isdescribed below. Referring back to FIG. 3, at 302, the access rulegeneration system 300 may determine the fraud detection performance ofeach child 410-419 of the root node 401 shown in FIG. 4. To determinethe performance of each child node 410-419, the access rule generationsystem 300 may determine a set of access requests from the accessrequest information 310 that have parameters satisfying the conditionsassociated with a particular node 410-419. The access rule generationsystem 300 may determine the performance for each particular node410-419 based on the validity information 320 of their correspondingaccess requests. The performance may be determined based on a“prediction error” percentage. The detection error percentage may bebased on the percentage of “false positives” (e.g., a legitimate accessrequest being determined to be fraudulent) and the percentage of “falsenegatives” (e.g., a fraudulent request being determined to belegitimate) for the conditions associated with a particular node. Asmentioned above, the validity information 320 may be adjusted at 301.For example, there are 100 access requests in total. In this example,the access rule generation system 300 may determine access requestsoutcomes for the 100 access requests based on condition X₂₂ (representedby node 414). The access rule generation system 300 may determine thenumber access request out of the 100 access requests that would begranted, and the number of access requests that would be denied, basedon whether condition X₂₂ (represented by node 414) is satisfied. In thisexample 10 of those 100 access requests outcomes are a false positive ora false negative. As such, the detection error percentage for splittingat node 414 may be 10%. Nodes having a lower detection error percentageare deemed to have higher performance compared to other nodes having agreater detection error percentage (e.g., fewer errors means betterperformance).

At 303, the access rule generation system 300 may select the bestperforming node (e.g., the node having the greatest fraud predictivepercentage) to split the decision tree. For example, referring to FIG.4, the access rule generation system 300 may determine that node 414associated with the condition X₂₂ has the highest performance (e.g., thesplit at node 414 has a lower detection error percentage compared to theother children nodes 410-413 and 415-419). Accordingly, the access rulegeneration system 300 may select node 414 to split the branch. As shownin FIG. 4, the solid line indicates the nodes add branches having thebest performance at each level while the dashed lines show the otherpossible nodes. In FIG. 4, there is a solid line connecting node 401 tonode 414 while nodes 410-413 and 415-419 are connected to node 401 bydashed lines.

The split at node 414 may be a binary split such that the left split isa first tree (containing nodes 420-423 in FIG. 4) where the condition ofthe best performing node (i.e., condition X₂₂ of node 414) is satisfiedand the right split is a second tree (containing nodes 424-427 in FIG.4) where the condition of the best performing node is not satisfied. Asshown in FIG. 4, the prime symbol (′) is used to indicate that thecorresponding condition is not satisfied. For example, the conditionlabeled X′₂₂ indicates that condition X₂₂ is not satisfied. From thebinary split at node 414, nodes 420-423 in the left split includecondition X₂₂ while nodes 424-427 in the right split include thecondition X′₂₂. As shown in FIG. 4, both the left split from node 414and the right split from node 414 are connected by solid lines,indicating the best performing branches of the tree.

At 304, after selecting the first node of the branch (e.g., node 414)beyond the root node 401 to split, the access rule generation system 300may then determine the performance of each of the nodes in the secondlevel of the tree (e.g., nodes 420-427), including the nodes in the leftsplit of node 414 (e.g., nodes 420-423) and the nodes in the right splitof node 414 (e.g., nodes 424-427).

As shown in FIG. 4, each node in the second level of the tree (nodes420-427) includes the conditions corresponding branch split. In FIG. 4,the conditions are shown below the node. For instance, the branchcomprising node 421 has the conditions of X₂₂X₁₂ since node 414, theparent of node 421, has condition X₂₂ and node 421 has the conditionX₁₂. In some embodiments, the children of node 414 may not includeconditions within the X₁₂ parameter since the node 414 is associatedwith a condition of that parameter (e.g., X₂₂). After building thebranches, the access rule generation system 300 may determine, for eachbranch, the access requests of the access request information 310 thatsatisfy the each of the conditions of the nodes included within thatbranch. Then the access rule generation system 300 may determine theperformance for each of the nodes in the second level of the tree (e.g.,nodes 420-427) based on the validity information 320 corresponding tothe access requests having parameters that satisfy the conditions of theparticular node (or, for right splits, where a particular condition isnot satisfied as indicated by the prime symbol).

At 305, the access rule generation system 300 may determine whether tocontinue building the current branch based on one or more stop criterion(e.g., the tree contains a certain number of levels, or when each of thenodes corresponds to only valid, or only invalid access requests). Ifthe access rule generation system 300 determines to continue buildingthe branch (e.g., the decision at 305 is YES), then the access rulegeneration system 300 may return to 303 to repeat the process ofselecting a node for building the tree and then determining, at 304, theperformance of the branches

The access rule generation system 300 may select a node to build thetree for each split of the tree (e.g., the left split of node 414 andthe right split of node 414). Referring to FIG. 4, the access rulegeneration system 300 may determine that node 421 (conditions of X₂₂X₁₂)has a higher performance than the other nodes within the left split ofnode 414 (i.e., nodes 420, 422, and 423). For the right split of node414, the access rule generation system 300 may determine that node 426is the highest performing node of the nodes within the right split(e.g., nodes 424-427).

At 305, the access rule generation system 300 may determine whether tocontinue building the tree based on the one or more stop criterion. Ifthe access rule generation system determines to continue building thetree, then the process selecting the best performing nodes for eachsplit repeats until the one or more stop criterion are met. As shown inFIG. 4, node 430 may be the best performing node in the left split ofnode 421, node 431 may be the best performing node in the right split ofnode 421, node 432 may be the best performing node in the left split ofnode 426, and node 433 may be the best performing node in the rightsplit of node 426.

Once the stop criterion are met, at 306 the access rule generationsystem 300 may generate candidate access rules 334 based on theconditions of the nodes for each split of the tree. Referring to FIG. 4,in one example the stop criterion may be a tree having three levels andthe best performing nodes for the four branches may be nodes 430, 431,432, and 433. Accordingly, the access rule generation system 300 maygenerate a first candidate access rule having conditions X₂₂X₁₂X₄₅, asecond candidate access rule having conditions X′₂₂X′₁₂X₆₃, a thirdcandidate access rule having conditions X′₂₂X₃₁₀X₁₇, and a fourthcandidate access rule having conditions X′₂₂X′₃₁₀X₅₃. The access rulegeneration system 300 may provide the candidate access rules 334 to anaccess server to be implemented for determining access request outcomes.

As discussed above, access rule generation system 300 may generatecandidate access rules using a decision tree (e.g., decision tree 400)by repeatedly determining the performance of children nodes and thenselecting a node to build the branch. This process may require a largeamount of computing resources to be expended. For instance, the accessrequest information 310 may include hundreds of thousands of accessrequests in order to have a representative sample of patterns offraudulent activity. At each node of a branch, all possible splits areevaluated based on the access request information 310. In addition, thenodes of each level down on the decision tree is dependent on nodes inthe previous levels of the tree. Therefore, the access rule generationsystem 300 may need to expend a large amount of computing resources ineach determination and comparison of node performance when building adecision tree since it requires the node performance to be determinedand compared numerous times. Therefore, the access rule generationsystem 300 may take a long time and may expend a large amount ofcomputing resources by generating candidate access rules using adecision tree. This complexity may be compounded in decision trees thatuse triple-splitting or quart-splitting compared to binary splittinglike the example in FIG. 4. The generation and selection of candidateaccess rules may be processed quicker and more efficiently usingsegmentation instead of a decision tree as further described below.

III. Rule Generation and Selection Based on Segmentation

Instead of generating access rules using a decision tree as discussedabove with reference to FIGS. 3 and 4, an access rule generation systemmay generate access rules using segmentation. By using mutuallyexclusive segments, the access rule generation system can generateindependent access rules that may be evaluated independently. Therefore,the access rule generation system can implement the access rulegeneration process in parallel, thereby making access rule generationquicker and more efficient compared to access rule generation processesusing a decision tree.

As further described below, generating access rules using segmentationmay involve selecting certain access request parameters and segmentingthose parameters into a plurality of mutually exclusive conditions. Eachaccess rule may have one condition from each of the selected parametersand access rules for each combination of conditions may be generated. Assuch, the access rules generated based using segmentation may begenerated and evaluated independently, thereby enabling the use ofsimultaneous parallel processing. Furthermore, generating access rulesusing a decision tree can require the performance evaluation at eachbranch split. In contrast, generating access rules using segmentationgenerates can generate each potential access rule first, and thenevaluate all of the potential access rules at once. Therefore, an accessrule generation system may generate access rules quicker and moreefficiently using segmentation compared to using a decision tree sincethe decision tree process is iterative and it cannot be performedsimultaneously.

A. System for Generating Access Rules Using Segmentation

FIG. 5 shows a functional block diagram of an access rule generationsystem 500 for generating and selecting access rules using segmentation,in accordance with some embodiments. The access rule generation system500 may operate similar to the access rule generation system 130 ofFIG. 1. The access rule generation system 500 may be implemented in aresource security system similar to the resource security system 100 ofFIG. 1 described above. As further described below, the access rulegeneration system 500 may generate candidate access rules 534 usingsegments based on access requests previously received by an accessserver and validity information corresponding to those access requests.The access rule generation system 500 may then provide the candidateaccess rules 534 to an access server to be used for determining accessrequest outcomes.

The access rule generation system 500 may store access requestinformation 510, validity information 520, and evaluation information550 as discussed herein. Before generating the access rules, at 501 theaccess rule generation system 500 may adjust the validity information520 using the evaluation information 550 to account for false positivesas discussed above.

In order to generate access rules using segmentation, at 502 the accessrule generation system 500 may select two or more parameters (e.g., tensor hundreds of parameters) from the access request parameters to use forsegmenting the access requests of the access request information 510.For example, at 502 the access rule generation system 500 may select onehundred parameters to use for segmenting the access requests of theaccess request information 510. The access rule generation system 500may select parameters that are sensitive to fraudulent access requests.For instance, some of the parameters may be selected based on theconditions of access rules currently implemented by an access server. Insome embodiments, instead of the access rule generation system 500selecting the parameters at 502, the parameters may be pre-selected.That is, the access rule generation system 500 may use pre-determinedparameters for generating and selecting access rules. The pre-determinedparameters may have been selected based on conditions that are known tobe indicative of fraud.

In one example, the access request information 510 may include accessrequests having a “user geographic location” parameter X₁, a “resourceamount” parameter X₂, a “day of the week” parameter X₃, a “time of day”parameter X₄, and a “request computer identifier” parameter X₅. In thisexample, the “user geographic location” parameter X₁ and the “resourceamount” parameter X₂ may have associated conditions that are the bestindicators of fraud and access rules may be generated having conditionsbased on these parameters. In other embodiments, the access requests mayhave different parameters. In other embodiments, the access rulegeneration system 500 may select a different number of parameters to usefor generation access rules.

After selecting the parameters, the access rule generation system 500may determine a plurality of conditions associated with each of theparameters (e.g., parameter X₁ and parameter X₂). For instance, the“user geographic location” parameter X₁ of an access request may have acategorical parameter value and the access rule generation system 500may associate conditions X₁₁, X₁₂, X₁₃, and X₁₄ with the “usergeographic location” parameter X₁ based on the different categories. Forexample, the condition X₁₁ may be satisfied by the parameter X₁ having aparameter value of “California,” the condition X₁₂ may be satisfied bythe parameter X₁ having a parameter value of “Arizona,” the conditionX₁₃, may be satisfied by the parameter X₁ having a parameter value of“Oregon,” and the condition X₁₄, may be satisfied by the parameter X₁having a parameter value of “Washington.”

The “resource amount” parameter X₂ of an access request may have anumerical parameter value and the access rule generation system 500 mayassociate conditions X₂₁, X₂₂, X₂₃, X₂₄, X₂₅ and X₂₆ based on numericalranges of values. For example, the condition X₂₁ may be satisfied by theparameter X₂ having a parameter value that is less than 100, thecondition X₂₂ may be satisfied by the parameter X₂ having a parametervalue that is greater than or equal to 100 but less than 500, thecondition X₂₃ may be satisfied by the parameter X₂ having a parametervalue that is greater than or equal to 500 but less than 2,000, thecondition X₂₄ may be satisfied by the parameter X₂ having a parametervalue that is greater than or equal to 2,000 but less than 5,000, thecondition X₂₅ may be satisfied by the parameter X₂ having a parametervalue that is greater than or equal to 5,000 but less than 20,000, andthe condition X₂₆ may be satisfied by the parameter X₂ having aparameter value that is greater than 20,000. In other embodiments,different threshold values may be used. The access rule generationsystem may determine the number of conditions and the ranges of theconditions or the number and range of the conditions may bepre-determined for a particular parameter.

After selecting the access request parameters (e.g., parameter X₁ andparameter X₂), at 503 the access rule generation system 500 may generatea plurality of potential access rules based on the parameters selectedat 502. The access rule generation system 500 may generate the pluralityof potential access rules such that each access rules has one conditionfrom each of the selected parameters and is independent from each of theother potential access rules. That is, the conditions of the pluralityof potential access rules are mutually exclusive. Since the access rulesare independent, the access rule generation system 500 may generate theplurality of access rules simultaneously, in parallel.

In some embodiments, after selecting the parameters at 502 but prior togenerating the access rules at 503, the access rule generation system300 may merge two or more conditions of related parameters. Mergingmultiple conditions into a single condition may reduce the computationcomplexity of running the access rules since there may be fewerconditions to check. For example, if both conditions X₂₁ and X₂₂ areselected, the condition X₂₁ being satisfied by the parameter X₂ having aparameter value that is less than 100, and the condition X₂₂ beingsatisfied by the parameter X₂ having a parameter value that is greaterthan or equal to 100 but less than 500, then conditions X₂₁ and X₂₂ maybe merged. The merged condition may be satisfied by parameter X₂ havinga parameter value that is less than 500 (e.g., the combination of theconditions X_(2<100) and 100<X_(2<500)).

B. Use of a Segmentation Diagram in Generating Access Rules

A segmentation diagram may be used to represent the mutually exclusiveconditions of the potential access rules generated at 503. FIG. 6 showsan exemplary segmentation diagram 600 for generating and selectingaccess rules, in accordance with some embodiments. The segmentationdiagram includes segments 601-620 corresponding to the conditions of theaccess rules generated at 503. For instance, segment 601 corresponds tothe condition X₁₁X₂₁, segment 602 corresponds to the condition X₁₁X₂₂,etc. As shown in FIG. 6, each of the segments are mutually exclusive.

The access rule generation system 500 may associate each access requestsof the access request information 510 with a particular segment 601-620based on the parameters of the access request. For instance, accessrequests having parameters that satisfy the conditions associated with aparticular segment 610-620 may be associated with that segment 601-620.

In the segmentation diagram 600, the access requests associated with acertain segment 601-620 may be represented by either an “X” mark or an“0” mark within that segment 601-620. The “X” mark represents afraudulent access request and an “0” mark represents a legitimate accessrequest. The access rule generation system 500 may determine whether aparticular access request is legitimate or fraudulent based on thevalidity information 520 corresponding to that access request. Forsimplicity, the segmentation diagram 600 only shows a few accessrequests for each segment 601-620. However, the access rule generationsystem 500 may generate access rules based on hundreds of thousands ofaccess requests or more. In some embodiments, instead of using the “X”and “0” marks, the access requests may be represented by a validityscore where 0.0 indicates a legitimate access request and 1.0 indicatesa fraudulent access request. In such embodiments, the validity scoresmay be adjusted by the access rule generation system (e.g., at 501) toaccount for false positives as described above.

Referring back to FIG. 5, at 504 the access rule generation system 500may determine the performance of each potential access rule. In order todetermine the performance of each potential access request, the accessrule generation server may determine a predictive percentage for eachsegment 601-620 based on the access requests within that segment601-620. As shown in the segmentation diagram 600 of FIG. 6, the segment601 representing the condition X₁₁X₂₁ includes one “X” mark and two “0”marks. Therefore, the access rule generation system 500 may determinethat that the predictive percentage for segment 601 is 33.33% (e.g., 1of 3). In addition, the access rule generation system 500 may determinethat predictive percentage for segment 602 is 0% (e.g., 0 of 4) and thatthat predictive percentage for segment 614 is 80% (e.g., 4 of 5) basedon the segmentation diagram 600. Since the segments 601-620 are mutuallyexclusive, each access request may only satisfy the conditions of asingle segment. Therefore, the access rule generation system maydetermine the performance (e.g., determine the predictive percentage) ofeach segment 601-620 simultaneously and in parallel.

After determining the performance of each segment 601-620, at 505 theaccess rule generation system 500 may select a plurality of candidateaccess rules 534 from the potential access rules. For example, theaccess rule generation system 500 may select the highest performingpotential access rules to be included in the set of candidate accessrules 534. For example, the access rule generation system 500 may selecta certain number of potential access rules or it may select potentialaccess rules having a predictive percentage greater than a particularthreshold value. The access rule generation system 500 may provide thecandidate access rules 534 to an access server to be implemented fordetermining access request outcomes.

C. Computer Performance Advantages from Using Segmentation

As discussed above, a decision tree may be used to generate and evaluatepotential access rules by building a branch of the tree incrementally,such that later steps are dependent on prior steps as discussed above.In contrast to the decision tree process, potential access rulesgenerated to correspond to mutually exclusive segments of conditionsallow for each of the potential access rules be to generated andevaluated independently of the others. Accordingly, the access rulegeneration system 500 may use a parallel computing process to generateand evaluate the potential access rules quickly and efficiently. Forexample, the access rule generation system 500 may implement a parallelcomputing framework (e.g., Apache Hadoop) for generating and selectingcandidate access rules using segmentation as discussed above withreference to FIGS. 5 and 6. As such, the access rule generation system500 may use a segmentation process to generate a set of candidate accessrules quicker and using fewer computational resources compared to theaccess rule generation system 300 which generates access rules usingdecision tree.

Furthermore, the process of generating and selecting candidate accessrules using segmentation is advantageous because it may only determinethe performance of each segment once while the process using a decisiontree repeatedly determines the performance of each node every time thata node is added to the branch. In addition, the complexity of thesegmentation process is based on the number of selected parameters andthe conditions within those parameters while a decision tree may operateon all of the parameters and condition. Since the access requestinformation 310, 510 may contain hundreds of thousands of accessrequests, determining and comparing the performance multiple times inthe generation of a single access rule using a decision tree may use asignificant amount of computing resources compared to a segmentationprocess. Furthermore, a segmentation process can operate based on asegmentation table indicating the performance of each segment while adecision tree process may operate on the entire set of access requestinformation. Therefore, the evaluating the performance of access rulesgenerated using segmentation may be more computationally efficientcompared to the generation of access rules using a decision tree for thesame access request information. Computational complexity for thesegmentation process may be further reduced by merging conditions of arelated parameter as discussed above.

IV. Exemplary Method for Access Rule Generation

FIG. 7 shows a flowchart 700 of a method for generating and selectingaccess rules using a computer system, in accordance with someembodiments. The method may be performed by a computer system, such asthe resource security system described herein. For example, the methodmay be performed by the resource security system 100 of FIG. 1 includingthe access rule generation system 130 and the access server 120. In oneexemplary embodiment, the access rule generation system may performsteps 701-707 and the access server may perform steps 708-711. In otherembodiments, the method may be performed by a single computer or server.In some embodiments, one or more of the method steps may not beperformed and the steps may be performed in a different order.

At 701, the computer system may store access request informationincluding a plurality of previous access requests, each previous accessrequest having a plurality of access request parameters. The pluralityof previous access request may have been previously received by anaccess server. The access request information may also indicate whetherthe access request outcome for a particular access request was reject,accept, or review.

At 702, the computer system may store validity information correspondingto the plurality of previous access requests, the validity informationindicating whether each access request is fraudulent or legitimate. Thevalidity information corresponding to a particular access request may bebased on the access request outcome for that access request. Thevalidity information may also be based on a report of fraudulent accessor a report of a denial of legitimate access.

In some embodiments, the computer system may determine false positivepercentages for access rules currently implemented by an access server.The computer system may then adjust the validity information for anaccess request based on the false positive percentages for access rulesthat would be triggered by that particular access request.

At 703, the computer system may select a first parameter and a secondparameter from the plurality of access request parameters, the firstparameter associated with a first set of conditions, the secondparameter associated with a second set of conditions For example, thecomputer system may select a first parameter X₁ and a second parameterX₂ as discussed above with reference to FIG. 5. In this example, thefirst parameter X₁ may indicate a “user geographic location” and thesecond parameter X₂ may indicate a “resource amount.” In someembodiments, more than two parameters may be selected from the pluralityof access request parameters. For example, the computer system mayselect tens or hundreds of parameters, or even all of from the pluralityof access request parameters.

At 704, the computer system may determine a plurality of mutuallyexclusive segments based on the first set of conditions and the secondset of conditions, each segment associated one condition of the firstset of conditions and one condition of the second set of conditions. Forexample, as shown in FIG. 6, the first parameter X₁ made include a setof 4 conditions including X₁₁, X₁₂, X₁₃, and X₁₄ and the secondparameter X₂ may include a set of 5 conditions including X₂₁, X₂₂, X₂₃,X₂₄, and X₂₅. Accordingly, the computer system may determine 20 mutuallyexclusive segments (e.g., segments 601-620 in FIG. 6) based on the firstset of 4 conditions and the second set of 5 conditions, where eachsegment has one condition from the first set and one condition from thesecond set.

At 705, the computer system may generate a plurality of potential accessrules, each potential access rule corresponding to a different segmentof the plurality of mutually exclusive segments, each of the potentialaccess rules having the conditions of the corresponding segment. Each ofthe potential access rules may be independent. That is, the conditionsof one potential access rule may be mutually exclusive to the conditionsof the other potential access rules. Since the access rules areindependent, the computer system may generate the plurality of accessrules simultaneously and in parallel.

At 706, the computer system may determine a predictive percentage foreach of the potential access rules based on the validity informationcorresponding to previous access requests having one or more parametersthat involve the conditions of the potential access rule. To determinethe predictive percentage for a potential access rule, the computersystem may determine a set access requests have parameters that satisfythe conditions of the potential access rule and then determine thepercentage of access requests in that set that are fraudulent. Theaccess requests corresponding to a particular may be represented as an“X” mark or an “0” mark as shown in FIG. 4. Since the segments aremutually exclusive, each access request may only satisfy the conditionsof one of the segments. Therefore, the access rule generation system maydetermine the predictive percentage for each of the potential accessrules simultaneously and in parallel.

At 707, the computer system may select one or more of the potentialaccess rule to be included in an operational set of access rules basedon the predictive percentages for each potential access rule. Forexample, computer system may select the highest performing potentialaccess rules to be included in a set of candidate access rules which maybe provided used in an operational set of access rules. The operationsset of access rules may then be used to determine an access requestoutcome for a newly received access request.

At 708, the computer system may receive a real-time access request. Forexample, the computer system may receive, over a network, a real-timeaccess request from a user device or an access device, via a resourcecomputer, as discussed above. The access request may include parametersof the access requests.

At 709, the computer system may obtain the operational set of accessrules from the system memory. The system memory may comprise RAM, ROM,EEPROM, or flash memory, for example. The system memory may containcode, for implementing the methods described herein. The system memorymay be load data from a computer-readable storage medium, such as a harddisk drive or a solid state drive. The system memory may also load datafrom network-accessible storage media, such as from a database server.

At 710, the computer system may use the operational set of access rulesto determine an access request outcome for one of the real-time accessrequests. The access request outcome may be based on a plurality ofaccess rule outcomes provided by the operational set of access rules asdescribed above. The access request outcome may indicate to accept,reject, or review the access request.

At 711, the computer system may provide access to the resource based onthe access request outcome. For example, the computer system may provideaccess to the resource if the access request outcome indicates to acceptthe access request. In another example, the computer system may notprovide access to the resource if the access request outcome indicatedto reject the access request.

V. Exemplary Computer Systems for Access Rule Generation andImplementation

The embodiments described above may involve implementing one or morefunctions, processes, operations or method steps. In some embodiments,the functions, processes, operations or method steps may be implementedas a result of the execution of a set of instructions or software codeby a suitably-programmed computing device, microprocessor, dataprocessor, or the like. The set of instructions or software code may bestored in a memory or other form of data storage element which isaccessed by the computing device, microprocessor, etc. In otherembodiments, the functions, processes, operations or method steps may beimplemented by firmware or a dedicated processor, integrated circuit,etc.

FIG. 8 shows a functional block diagram 800 of components of anexemplary computer system including an access rule generation system 830and an access server 820, in accordance with some embodiments. Thevarious components may be embodied by computer hardware or computer codestored on a non-transitory computer readable storage medium.

The access rule generation system 830 may comprise one or more processorcircuits 831. The processor circuits 831 may execute instructions toperform the functions of the access rule generation systems describedherein (e.g., generating and selecting access rules). The processorcircuits 831 may be configured for parallel processing of data. Theprocessor circuits 831 may be coupled to one or more memory units 832that are configured to store data and instructions. The memory units 832may be non-transitory computer-readable storage medium.

The processor circuits 831 may read data from the memory units 832 andwrite data to the memory units 832. For example, the processor circuits831 may load into the memory units 832 a plurality of access requestinformation, validity information, evaluation information, informationrelated access rule performance, and information related to access rulegeneration, and information related to access rule selection asdescribed herein.

The access rule generation system 830 may also comprise a communicationinterface 833. The communication interface 833 may receivecommunications from a communication interface of another computer, suchas communications from a resource computer or an access server. Thecommunication interface 833 may also transmit communications to anothercomputer. As described herein, the access rule generation system 830 mayreceive access request information, validity information, evaluationinformation, from a resource computer or an access server.

The access rule generation system 830 may also comprise one or morestorage drives 834. The storage drives 834 may be directly coupled tothe access rule generation system 830 or they may be network accessstorage drives 834. The storage drives 834 may comprise one or moredatabases for storing the access request information, the validityinformation, and the evaluation information described herein. Thestorage drives 834 may store data that may be loaded into the memoryunits 832 by the processor circuits 831.

The access server 820 may comprise one or more processor circuits 821.The processor circuits 821 may execute instructions to perform thefunctions of the access servers described herein (e.g., operating accessrules to accept, reject, or review access requests). The processorcircuits 821 may be coupled to one or more memory units 822 that areconfigured to store data and instructions. The memory units 822 may benon-transitory computer-readable storage medium. The processor circuits821 may read data from the memory units 822 and write data to the memoryunits 822. For example, the processor circuits 821 may load into thememory units 822 a plurality of access request rules and parameters ofan access request in order to determine an access request outcome, asdescribed herein.

The access server 820 may also comprise a communication interface 823.The communication interface 823 may receive communications from acommunication interface of another computer, such as communications froma resource computer or an access server. The communication interface 823of the access server 820 may communicate with the communicationinterface 823 of the access rule generation system 830. Thecommunication interface 823 may also transmit communications to anothercomputer. The access server 820 may receive access request informationand access request parameters via the communication interface 823.

The access server 820 may also comprise one or more storage drives 824.The storage drives 824 may be directly coupled to the access server 820or they may be network accessible storage drives 824. The storage drives824 may comprise one or more databases for storing the access requestinformation and the access request parameters. The storage drives 824may store data that may be loaded into the memory units 832 by theprocessor circuits 821.

The above description is illustrative and is not restrictive. Manyvariations of the invention may become apparent to those skilled in theart upon review of the disclosure. The scope of the invention may,therefore, be determined not with reference to the above description,but instead may be determined with reference to the pending claims alongwith their full scope or equivalents.

It should be understood that any of the embodiments of the presentinvention can be implemented in the form of control logic using hardware(e.g. an application specific integrated circuit or field programmablegate array) and/or using computer software with a generally programmableprocessor in a modular or integrated manner. As used herein, a processorincludes a single-core processor, multi-core processor on a sameintegrated chip, or multiple processing units on a single circuit boardor networked. Based on the disclosure and teachings provided herein, aperson of ordinary skill in the art will know and appreciate other waysand/or methods to implement embodiments of the present invention usinghardware and a combination of hardware and software.

Any of the software components or functions described in thisapplication may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example,Java, C, C++, C#, Objective-C, Swift, or scripting language such as Perlor Python using, for example, conventional or object-orientedtechniques. The software code may be stored as a series of instructionsor commands on a computer readable medium for storage and/ortransmission. A suitable non-transitory computer readable medium caninclude random access memory (RAM), a read only memory (ROM), a magneticmedium such as a hard-drive or a floppy disk, or an optical medium suchas a compact disk (CD) or DVD (digital versatile disk), flash memory,and the like. The computer readable medium may be any combination ofsuch storage or transmission devices.

Storage media and computer-readable media for containing code, orportions of code, can include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information such as computer-readable instructions, data structures,program modules, or other data, including RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disk (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, data signals, datatransmissions, or any other medium which can be used to store ortransmit the desired information and which can be accessed by thecomputer. Based on the disclosure and teachings provided herein, aperson of ordinary skill in the art will appreciate other ways and/ormethods to implement the various embodiments.

Such programs may also be encoded and transmitted using carrier signalsadapted for transmission via wired, optical, and/or wireless networksconforming to a variety of protocols, including the Internet. As such, acomputer readable medium according to an embodiment of the presentinvention may be created using a data signal encoded with such programs.Computer readable media encoded with the program code may be packagedwith a compatible device or provided separately from other devices(e.g., via Internet download). Any such computer readable medium mayreside on or within a single computer product (e.g. a hard drive, a CD,or an entire computer system), and may be present on or within differentcomputer products within a system or network. A computer system mayinclude a monitor, printer, or other suitable display for providing anyof the results mentioned herein to a user.

Any of the methods described herein may be totally or partiallyperformed with a computer system including one or more processors, whichcan be configured to perform the steps. Thus, embodiments can bedirected to computer systems configured to perform the steps of any ofthe methods described herein, potentially with different componentsperforming a respective steps or a respective group of steps. Althoughpresented as numbered steps, steps of methods herein can be performed ata same time or in a different order. Additionally, portions of thesesteps may be used with portions of other steps from other methods. Also,all or portions of a step may be optional. Additionally, any of thesteps of any of the methods can be performed with modules, units,circuits, or other means for performing these steps.

The specific details of particular embodiments may be combined in anysuitable manner without departing from the spirit and scope ofembodiments of the invention. However, other embodiments of theinvention may be directed to specific embodiments relating to eachindividual aspect, or specific combinations of these individual aspects.

The above description of example embodiments of the invention has beenpresented for the purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdescribed, and many modifications and variations are possible in lightof the teaching above.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary. The use of “or” isintended to mean an “inclusive or,” and not an “exclusive or” unlessspecifically indicated to the contrary.

All patents, patent applications, publications, and descriptionsmentioned herein are incorporated by reference in their entirety for allpurposes. None is admitted to be prior art.

What is claimed is:
 1. A method for generating access rules, the methodcomprising performing by a computer system: selecting a first parameterand a second parameter from a plurality of access request parameters ofa plurality of previous access requests, the first parameter associatedwith a first set of conditions, the second parameter associated with asecond set of conditions; determining a plurality of mutually exclusivesegments based on the first set of conditions and the second set ofconditions, each segment associated one condition of the first set ofconditions and one condition of the second set of conditions; generatinga plurality of potential access rules, each potential access rulecorresponding to a different segment of the plurality of mutuallyexclusive segments, each of the potential access rules having theconditions of the corresponding segment; determining a predictivepercentage for each of the potential access rules based on validityinformation corresponding to previous access requests having one or moreparameters that involve the conditions of the potential access rule; andselecting one or more of the potential access rules to be included in anoperational set of access rules based on the predictive percentages foreach of the potential access rules, wherein the selected one or more ofthe potential access rules are included in the operational set of accessrules, wherein the operational set of access rules is loaded into asystem memory, and wherein the operational set of access rules is usedto determine an access request outcome for a real-time access requestfor a resource.
 2. The method of claim 1, wherein the plurality ofpotential access rules are generated simultaneously in parallel, andwherein the predictive percentages for the plurality of potential accessrules are determined simultaneously in parallel.
 3. The method of claim1, wherein each of the plurality of previous access requests hasparameters that involve the conditions of a single potential access ruleof the plurality of potential access rules.
 4. The method of claim 1,further comprising: determining the first set of conditions based onparameter values of the first parameter, each of the conditions of thefirst set of conditions being mutually exclusive to the other conditionsof the first set of conditions; and determining the second set ofconditions based on parameter values of the second parameter, each ofthe conditions of the second set of conditions being mutually exclusiveto the other conditions of the second set of conditions.
 5. The methodof claim 1, further comprising: determining, for each of the potentialaccess rules, a set of previous access requests of the plurality ofprevious access requests having access request parameters that involvethe conditions of the potential access rule; and determining, for eachof the sets of previous access requests, the validity informationcorresponding to each of the previous access requests in the set ofprevious access requests, wherein the determining of the predictivepercentage for each of the potential access rules is based on thevalidity information corresponding to each of the previous accessrequests in the set of previous access requests.
 6. The method of claim1, further comprising: receiving, over a network from a first device, afirst access request having access request parameters; accessing thesystem memory to obtain the operational set of access rules in responseto receiving the first access request; determining a first accessrequest outcome for the first access request based on a first accessrule and the access request parameters of the first access request, theaccess request outcome for the first access request indicating to rejectthe first access request; determining to accept the first access requestfor evaluation of the first access rule; and providing access to theresource based on determining to accept the first access request.
 7. Themethod of claim 6, further comprising storing evaluation information inresponse to the determination to accept the first access request, theevaluation information including an identifier of the first accessrequest and an identifier of the first access rule.
 8. The method ofclaim 7, further comprising: receiving a report of fraudulent access tothe resource, the fraudulent access resulting from the first accessrequest; and adjusting validity information corresponding to the firstaccess request based on the report of fraudulent access.
 9. The methodof claim 8, further comprising: determining a false positive percentagefor the first access rule based on the evaluation information and thereport of fraudulent access; and adjusting the validity informationcorresponding to previous access requests that were rejected based onthe first access rule using the false positive percentage for the firstaccess rule, wherein the adjusted validity information is used in thedetermining of the predictive percentage for each of the potentialaccess rules.
 10. The method of claim 1, further comprising: includingthe one or more of the potential access rules in the operational set ofaccess rules; loading the operational set of access rules into thesystem memory; receiving, over a network from a plurality of devices, aplurality of real-time access requests; accessing the system memory toobtain the operational set of access rules when one of the plurality ofreal-time access requests is received from a first device of theplurality of devices; using the operational set of access rules todetermine the access request outcome for the real-time access request;and providing access to the resource based on the access requestoutcome.
 11. A computer system, comprising: a computer readable storagemedium storing a plurality of instructions; and one or more processorsfor executing the instructions stored on the computer readable storagemedium to: select a first parameter and a second parameter from aplurality of access request parameters of a plurality of previous accessrequests, the first parameter associated with a first set of conditions,the second parameter associated with a second set of conditions;determine a plurality of mutually exclusive segments based on the firstset of conditions and the second set of conditions, each segmentassociated one condition of the first set of conditions and onecondition of the second set of conditions; generate a plurality ofpotential access rules, each potential access rule corresponding to adifferent segment of the plurality of mutually exclusive segments, eachof the potential access rules having the conditions of the correspondingsegment; determine a predictive percentage for each of the potentialaccess rules based on validity information corresponding to previousaccess requests having one or more parameters that involve theconditions of the potential access rule; and select one or more of thepotential access rules to be included in an operational set of accessrules based on the predictive percentages for each of the potentialaccess rules, wherein the selected one or more of the potential accessrules are included in the operational set of access rules, wherein theoperational set of access rules is loaded into a system memory, andwherein the operational set of access rules is used to determine anaccess request outcome for a real-time access request for a resource.12. The computer system of claim 11, wherein the plurality of potentialaccess rules are generated simultaneously in parallel, and wherein thepredictive percentages for the plurality of potential access rules aredetermined simultaneously in parallel.
 13. The computer system of claim11, wherein each of the plurality of previous access requests hasparameters that involve the conditions of a single potential access ruleof the plurality of potential access rules.
 14. The computer system ofclaim 11, further comprising instructions to: determine the first set ofconditions based on parameter values of the first parameter, each of theconditions of the first set of conditions being mutually exclusive tothe other conditions of the first set of conditions; and determine thesecond set of conditions based on parameter values of the secondparameter, each of the conditions of the second set of conditions beingmutually exclusive to the other conditions of the second set ofconditions.
 15. The computer system of claim 11, further comprisinginstructions to: determine, for each of the potential access rules, aset of previous access requests of the plurality of previous accessrequests having access request parameters that involve the conditions ofthe potential access rule; and determine, for each of the sets ofprevious access requests, the validity information corresponding to eachof the previous access requests in the set of previous access requests,wherein the determining of the predictive percentage for each of thepotential access rules is based on the validity informationcorresponding to each of the previous access requests in the set ofprevious access requests.
 16. The computer system of claim 11, furthercomprising instructions to: receive, over a network from a first device,a first access request having access request parameters; access thesystem memory to obtain the operational set of access rules in responseto receiving the first access request; determine a first access requestoutcome for the first access request based on a first access rule andthe access request parameters of the first access request, the accessrequest outcome for the first access request indicating to reject thefirst access request; determine to accept the first access request forevaluation of the first access rule; and providing access to theresource based on determining to accept the first access request. 17.The computer system of claim 16, further comprising instructions tostore evaluation information in response to the determination to acceptthe first access request, the evaluation information including anidentifier of the first access request and an identifier of the firstaccess rule.
 18. The computer system of claim 17, further comprisinginstructions to: receive a report of fraudulent access to the resource,the fraudulent access resulting from the first access request; andadjust validity information corresponding to the first access requestbased on the report of fraudulent access.
 19. The computer system ofclaim 18, further comprising instructions to: determine a false positivepercentage for the first access rule based on the evaluation informationand the report of fraudulent access; and adjust the validity informationcorresponding to previous access requests that were rejected based onthe first access rule using the false positive percentage for the firstaccess rule, wherein the validity information is used in the determiningof the predictive percentage for each of the potential access rules. 20.The computer system of claim 11, further comprising instructions to:include the one or more of the potential access rules in the operationalset of access rules; load the operational set of access rules into thesystem memory; receive over a network from a plurality of devices, aplurality of real-time access requests; access the system memory toobtain the operational set of access rules when one of the plurality ofreal-time access requests is received from a first device of theplurality of devices; use the operational set of access rules todetermine the access request outcome for the real-time access request;and provide access to the resource based on the access request outcome.